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sanhao-global-experts

expense-summary-tool

Save hours every week. This expense summary tool toolkit gives you a battle-tested prompt and operating playbook for restaurant/brand growth. No setup, works in any LLM chatbot.

Input Schema

NameRequiredDescriptionDefault
queryNoOptional user query to scope the analysis.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

D1.7/5.0
Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden and delivers none of it. It says nothing about what the tool reads, what it returns, whether it mutates anything, or what the 'playbook' framing implies for output shape.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

It is short, but all three sentences are promotional filler that earn no place in a tool definition. Nothing is front-loaded about the actual operation, so brevity here reflects missing content rather than efficiency.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no annotations, no output schema, and only a single optional parameter, the description is the sole source of behavioral information and it supplies none. An agent cannot tell what calling this tool produces or when it is the right choice among the many adjacent expense tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single 'query' parameter is fully documented in the schema (100% coverage), so the baseline of 3 applies. The description adds no meaning about how a query scopes the analysis, but the schema already covers the semantics adequately.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description never states what the tool actually does with expenses. Instead it restates the name ('expense summary tool toolkit') and pivots to unrelated marketing copy about a 'battle-tested prompt and operating playbook for restaurant/brand growth,' which does not describe an expense summarization capability and gives no way to distinguish this from the many expense-* siblings such as expense-audit-tool or expense-summary-tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use guidance, no alternatives named, and no exclusions. 'No setup, works in any LLM chatbot' is a sales claim, not a usage condition, so an agent has nothing to route on.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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